Modern global cellular and non-cellular positioning technologies are based on generating large global databases containing information on cellular and non-cellular communication network nodes, e.g. cellular radio network base stations (BSs) or non-cellular radio network, e.g. WLAN, access points (APs), and their signals. The information may originate entirely or partially from users of these positioning technologies acting as data collectors.
The data provided by these data collectors, generally mobile terminals, is typically in the form of “fingerprints”, which contain a location information, e.g. obtained based on received satellite signals of a global navigation satellite system (GNSS), and radio measurement values, i.e. measurements of radio parameters. In addition, a fingerprint may comprise communication network node identification information identifying a node that is observed by the collector and being associated with the radio measurement values pertaining to that node.
This data may then be transferred to a server or cloud, where the data (usually of a multitude of users) may be collected and where a radiomap for positioning purposes may be generated (or updated) based on the data.
In the end, this radiomap may be used for estimating a position, e.g. the position of a mobile terminal. This may function in two modes. The first mode is the terminal-assisted mode, in which the mobile terminal performs the measurements of radio parameters to obtain radio measurement values via a cellular and/or non-cellular air interface, provides the measurements to a remote server, which in turn, based on the radiomap, determines and provides the position estimate back to the mobile terminal The second mode is the terminal-based mode, in which the mobile terminal has a local copy of the radiomap (or only a subset of a global radiomap), e.g. downloaded by the mobile terminal from a remote server or pre-installed in the mobile terminal.
The actual position estimate may then be obtained based on the radiomap or parts thereof by obtaining identification information of nodes that are observed at the respective position and/or obtaining radio measurement values at that position.
Based on the radiomap or parts thereof, properties of a respective node may be modeled. The model may then be used for position estimation. For instance, the coverage area of nodes may be modeled. For each node that is observed at the respective position, the modeled coverage area may be considered and the position estimate may then be the center of the area of intersection of the coverage area models of all observed nodes. As an alternative to coverage area models (or as an addition allowing more accurate position estimation), also radio channel models (aka radio propagation models) for communication network nodes may serve as a basis for determining a position based on, for instance, a received signal strength and/or a path loss measured at the respective position. A radio channel model may for instance describe how the power of a signal emitted by a communication network node decays with increasing distance from the communication network, for instance under consideration of further parameters as for instance the radio transmission frequency. Now, if radio channel model information is available for an identified communication network node, for instance if a strength of a signal from this communication network node as received at the respective position (or, as another example, the path loss experienced by this signal) has been measured at that position, an estimate of the distance towards the communication network node can be determined and exploited (e.g. among further information) to determine a position estimate.